气候变暖对黑龙江省农作物结构调整影响及未来50年农业情景对策

在未来30、50年气温将增高1．9℃、2．4℃情景下,积温带向北推移近5个纬距,2050年,原第1积温带北移至大兴安岭北部,其余4个积温带基本消失。气候变暖将使黑龙江省主栽农作物水稻、小麦、玉米、大豆等种植区域和模式发生变化。因此提出了未来适应农业发展的6项对策,特别是主要作物结构调整及区域分布。     

长春市气温变化与城市化影响分析

本文利用长春市1951-2005年气温资料,分析了长春市平均气温、平均最高气温及平均最低气温的变化。结果表明：在全球气候变暖的背景下,长春市的气温也在变暖,而且90年代以来增温十分明显。长春市1951-2000年50年的平均气温以0．36℃／10a的倾向率上升,1991—2000年气温上升加剧,倾向率达到0．460C／10a,明显高于全国平均水平。     

1980-2008年黑龙江省气候变暖及其对大豆种植的影响

基于黑龙江省10个农业气象观测站1980-2008年地面观测田平行观测资料和逐日气象资料,运用气候倾向率、M-K检测和统计回归等方法,分析研究区表征气候变暖的主要气候要素的时空变化规律以及气候变暖对大豆的影响。结果表明：1980-2008年,研究区气候出现明显变暖趋势,年平均气温升高,热量增加,无霜期延长,且区域间存在差异,南部地区热量资源增加显著。大豆百粒重随9月平均气温的升高而增加,却随年平均气温的升高而下降,表明秋季增温对大豆产量有正效应,而年平均气温的升高对大豆产量存在负作用。气候变暖对大豆生产的影响是利弊兼存,在调整种植布局时应给予重点关注。     

1960-2009年咸宁市气候变化特征分析

利用1960-2009年咸宁市3个地面气象站气象资料,统计分析近50 a来该区域气温、降水等主要气候要素的年变化、四季变化及年代际变化的趋势特征。结果表明：近50 a研究区气温有上升趋势,气候倾向率为0.23℃/10a,年平均气温在20世纪90年代末发生突变。春秋季平均气温分别在2002年和1999年发生突变,夏季平均气温在2006年发生突变,冬季平均气温早在1990年发生突变。春季与秋季平均气温的变化比较一致,冬季平均气温对全球变暖响应最敏感,春秋与秋季对气候变暖的响应是比较敏感,而夏季对气候变暖的响应最为迟缓。近50 a年降水量呈波动但无明显增降的趋势,其中春夏两季变化趋势较为一致并有下降的趋势,且春夏降水量的变化主导着年降水量的变化;而冬季降水量有上升的趋势。通过对气温与降水变化趋势的比较,发现冬季对气候变化的响应最显著、其余季节无明显相关性。     

气候变暖对临沂农业的影响

对临沂 1961-2006 年的气候资料进行统计分析,深入的研究了气候变暖对临沂农业的影响.结果表明临沂市年平均气温明显上升,冬春季气温在波动中上升明显,夏季几乎无变化,临沂气温升高主要是最低气温升高所致,自 1990s 以来,暖冬现象十分严重;≥O℃的积温经历下降再上升的过程,近 16 a 来上升最明显;霜冻终日提前、初日推后,无霜冻期天数增多;临沂的春播期提前,秋播期推迟.农业气象灾害加剧.气候变暖对冬小麦生产利大于弊,对水稻、玉米生产不利.喜温作物面积扩大,复种指数提高,种植制度变为一年两熟制.气候变暖对临沂农业影响是利弊并存.     

黑龙江省近10a气温预报模拟检验与未来40a气温预测的分析

使用近10 a气温降水资料,采用CCCma、Ccsr、Gfdl、Csiro和Hadley海-气数值模式对哈尔滨、齐齐哈尔、牡丹江、佳木斯和4市平均的2000、2009年平均气温变化进行模拟预报,对模拟结果进行气候态方法检验。结果表明,部分气候模式模拟的气温气候预报检验达到可信的程度,可以使用其结果作延伸预报;2010-2050年气候模拟预报结果表明未来的40 a年平均气温累计上升1.1℃。     

近57年资源县山区冬季气候变暖特征分析

利用资源县1961~2017年逐日气温观测资料,应用线性倾向估计、t检验及M-K突变检验法对资源县57年冬季气候变暖特征进行了分析。结果表明:近57年资源县冬季、年平均气温上升趋势显著,线性倾向率为0.276、0.19℃/10a,冬季气候变暖趋势明显,对全年气候变暖贡献较大;2月份平均气温显著上升,线性倾向率为0.419℃/10a,对冬季变暖贡献较大;极端最低气温上升趋势更为显著,线性倾向率为0.448℃/10a,对冬季增温影响最显著;冬季平均气温的突变点发生在1996年;20世纪1960~1980年代为冬季低温期,冷冬大多出现在1980年代之前,暖冬1990年代之后呈明显增加趋势。     

肇庆市近54a气温变化特征分析

采用统计分析方法、Mann-Kendall法和小波分析等方法,对1961~2014年肇庆市6个区域气象观测站的年平均气温、季平均气温、年最高气温和年最低气温等气候要素作了较全面的分析。结果表明:近54a来肇庆市6个区域年平均气温呈显著上升趋势,增温速率最高为广宁县,0.24℃.(10a)-1,最低为怀集县,0.11℃.(10a)-1;季平均气温变化幅度最大的是秋季,其次为冬季,变化幅度最小为夏季;年最高气温除怀集县呈下降趋势,其余5个区域均呈上升趋势,而年最低气温6个区域均呈显著上升趋势;肇庆市气候变暖主要是由秋季和冬季的升温增暖造成的;近54a来封开县发生两次气温突变,其余地区在80到90年代先后发生增温性突变;周期分析显示,肇庆市年平均气温均具有30a、12a、8a和5a的周期性特征。     

1961—2013年石家庄市气温变化特征分析

文章利用石家庄市1961—2013年气温资料,采用滑动平均、线性趋势图、M-K突变检验等方法对石家庄近53a的气温变化特征进行了分析。结果表明:近53a平均气温上升趋势明显,20世纪80年代后期升温显著;年平均最高气温增温率仅为0.107℃/10a,增温趋势平缓,而年平均最低气温增温率为0.594℃/10a,呈明显的逐年上升趋势,说明气候变暖趋势显著;高温日数的增加,气候变暖趋势已成为必然。四季平均气温呈线性上升趋势,春季、冬季变化幅度最大且具有继续升温的趋势,是造成气候变暖的主要原因。而夏季、秋季变化幅度较小。     

1960—2009年咸宁市气候变化特征

利用1960—2009年咸宁市3个地面气象站气象资料,统计分析近50 a来该区域气温、降水等主要气候要素的年变化、四季变化及年代际变化的趋势特征。结果表明：近50 a研究区气温有上升趋势,气候倾向率为0.23℃/10 a,年平均气温在20世纪90年代末发生突变。春秋季平均气温分别在2002年和1999年发生突变,夏季平均气温在2006年发生突变,冬季平均气温在1990年发生突变。春季与秋季平均气温的变化较一致,冬季平均气温对全球变暖响应最敏感,春季与秋季对气候变暖的响应较敏感,而夏季对气候变暖的响应最为迟缓。近50 a咸宁市年降水量呈波动但无明显增降的趋势,其中春夏两季变化趋势较为一致并有下降的趋势,且春夏降水量的变化主导着年降水量的变化;而冬季降水量有上升的趋势。通过对气温与降水变化趋势的比较,发现冬季对气候变化的响应最显著,其余季节无明显相关性。     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.     

VARIABILITY OF INTER-ANNUAL RELATIONSHIP BETWEEN INDIAN OCEAN DIPOLE AND HUAXI REGION’S AUTUMN PRECIPITATION

The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region.     

A COMPARATIVE ANALYSIS OF ATMOSPHERIC AND OCEANIC CONDITIONS BEFORE THE OCCURRENCE OF TWO TYPES OF EL NIO EVENTS

The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o.     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.     

全球贸易隐含碳变化及其影响分析

基于最新的GTAP8 (Global Trade Analysis Project）数据库,使用投入产出法,分析了2004年到2007年全球贸易变化下南北集团贸易隐含碳变化及对全球碳排放的影响。结果显示,随着发展中国家进出口规模扩张,全球贸易隐含碳流向的重心逐渐向发展中国家转移。2004年到2007年,发达国家高端设备制造业和服务业出口以及发展中国家资源、能源密集型行业及中低端制造业出口的趋势加强,该过程的生产转移导致全球碳排放增长4.15亿t,占研究时段全球贸易隐含碳增量的63%。未来发展中国家的出口隐含碳比重还将进一步提高。贸易变化带来的南北集团隐含碳流动变化对全球应对气候变化行动的影响日益突出,发达国家对此负有重要责任。     

Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery

Hourly outgoing longwave radiation(OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite(COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm(OLR12.0using the 12.0 μm channel) and three multiple-channel algorithms(OLR10.8+12.0using the 10.8 and 12.0 μm channels; OLR6.7+10.8using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System(CERES) over the full COMS field of view [roughly(50°S–50°N, 70°–170°E)] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5–7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8and OLR All have much smaller errors(～ 6 W m-2) than OLR12.0and OLR10.8+12.0(～ 8 W m-2). Moreover, the small errors of OLR6.7+10.8and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any     

Index to Vol.31

正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang;